Britain Breathing: Using the Experience Sampling Method to Collect the Seasonal Allergy Symptoms of a Country
Research output: Research - peer-review › Article
Abstract
Objective: Allergies are increasing, but the reasons for this are unclear. Although environmental factors are thought to be important, there is lack of data on how they contribute to symptom development. To understand this relationship better, we need accurate data about both symptoms and environmental factors. Our objective here is to ascertain whether experience sampling is a reliable approach for collecting allergy symptom data in the general population, allowing us to map symptoms and understand aetiology.
Materials and methods: We conducted a 32-week cross-sectional study where individuals reported their seasonal allergy symptoms and severity via a mobile application. Symptom geographical location and timestamp were also collected automatically.
Results: The experience sampling method reliably infers the incidence of seasonal allergies as indicated by the strong correlation (r = 0.93, p < 0.003) between the reported lack of wellness and the number of antihistamines prescribed by GPs.
Discussion and conclusion: The project has resulted in the first dataset to map allergy symptoms over time and place and reveals periods of peak hay fever symptoms in the UK.
Materials and methods: We conducted a 32-week cross-sectional study where individuals reported their seasonal allergy symptoms and severity via a mobile application. Symptom geographical location and timestamp were also collected automatically.
Results: The experience sampling method reliably infers the incidence of seasonal allergies as indicated by the strong correlation (r = 0.93, p < 0.003) between the reported lack of wellness and the number of antihistamines prescribed by GPs.
Discussion and conclusion: The project has resulted in the first dataset to map allergy symptoms over time and place and reveals periods of peak hay fever symptoms in the UK.
Bibliographical metadata
Original language | English |
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Pages (from-to) | 88-92 |
Number of pages | 4 |
Journal | Journal of the American Medical Informatics Association |
Volume | 25 |
Issue number | 1 |
Early online date | 12 Dec 2017 |
DOIs | |
State | Published - 1 Jan 2018 |